{"id":"W4229444393","doi":"10.18280/ts.390240","title":"Combined Spatial-Spectral Hyperspectral Image Classification Based on Adaptive Guided Filtering","year":2022,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Remote-Sensing Image Classification","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Hyperspectral imaging; Artificial intelligence; Pattern recognition (psychology); Support vector machine; Local binary patterns; Computer science; Classifier (UML); Contextual image classification; Discriminative model; Pixel; Computer vision; Histogram; Image (mathematics)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003208002,0.0002828628,0.0002239568,0.0002356539,0.0002694803,0.0000824523,0.0002569287,0.00004587035,0.00106096],"category_scores_gemma":[0.00001839972,0.0003318226,0.0001233366,0.0002829612,0.00005914304,0.0001528603,0.00003075255,0.0003508026,0.00006344474],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008206967,"about_ca_system_score_gemma":0.0000471514,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002609171,"about_ca_topic_score_gemma":0.000004297244,"domain_scores_codex":[0.9980788,0.0001317766,0.0004261184,0.0003939253,0.0005634406,0.000405972],"domain_scores_gemma":[0.9992855,0.00008522057,0.00009716074,0.0003682126,0.00006143527,0.0001024309],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002101928,0.0002218021,0.00008773259,0.00002688632,0.00005127789,0.00003398556,0.0003830752,0.2162662,0.7714342,0.001177239,0.005076886,0.005030476],"study_design_scores_gemma":[0.001258429,0.0004039464,0.0177702,0.00001729883,0.0000295664,0.000007055377,0.0002087909,0.9494143,0.02971118,0.0001636681,0.0006662403,0.0003493321],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3823158,0.00002708261,0.5955885,0.00164823,0.0009138873,0.001286683,0.0001190069,0.001555248,0.01654556],"genre_scores_gemma":[0.9906912,0.000002142172,0.008584227,0.000162083,0.0001670111,0.00008485319,0.0001648112,0.00007976521,0.00006384406],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7417231,"threshold_uncertainty_score":0.9999134,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03059735791223052,"score_gpt":0.2297470739108514,"score_spread":0.1991497159986209,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}